Ponzi Radar
Analyzes suspicious investment websites to score Ponzi and pyramid scheme risks using passive OSINT and evidence-checked analysis.
Ponzi Radar evaluates suspicious investment websites—such as crypto platforms promising guaranteed yields or multi-level referral networks—to generate an evidence-backed risk dossier. Combining a deterministic Python DAG pipeline with an MCP server interface, it safely inspects targets via passive headless browsing and gathers public records from RDAP, DNS, Certificate Transparency, the Wayback Machine, and corporate or regulatory databases like Brazil's CVM and BCB. Working alongside Claude to address contextual open questions, every citation is verified against archived artifacts with SHA-256 chain-of-custody tracking. The resulting dossier determines both a risk probability score (0–34) across a 15-item heuristic matrix and an operational life-cycle stage (E0–E7).